The demand and growth of wireless communication services has exceeded all its expectations and even more market is expected to be created. So far, speech transmission was the most important part of mobile communications. However, future trends in wireless communications will demand reliable and fast transmission of data and video, Internet browsing and the like. Thus, high data rates of several Megabits per second will be required. At the same time, the trends in design of mobile units are moving towards smaller light weight pocket communicators. Therefore, mobile units need to remain simple in order to enable a practical construction.
Knowledge of the fact that increasing the code word length of block codes or constraint length of convolutional codes leads to better performance dates back to Shannon's theory. It is also well known that maximum-likelihood (ML) decoding leads to the drawback that the performance gain is obtained at the expense of increased complexity up to the point where decoding becomes physically unrealizable. Thus, the research in coding theory over the years has seen many proposals aiming at constructing powerful codes with large equivalent block or constraint lengths structured so as to permit breaking the ML decoding into simpler partial decoding steps.
Turbo codes have been proposed by C. Berrou et al, “Near Shannon limit error-correction coding and decoding: Turbo codes”, Proc. IEEE ICC'93, May 1993 as the result of a clever intuition built on several concepts already established. Turbo codes were originally introduced as binary error-correction codes built from a parallel concatenation of two recursive systematic convolutional codes exploiting a suboptimal but very powerful iterative decoding algorithm, the so-called Turbo decoding algorithm. However, it has turned out that the method applied for this parallel concatenation is much more general. The Turbo principle is nowadays successfully applied to many detection/decoding problems such as serial concatenation, equalization, coded modulation, multi-user detection, joint interference suppression and decoding.
Attempts to combine Turbo codes with multi-level amplitude/phase modulations in order to improve transmission spectral efficiency has led to many proposals of so-called Turbo Coded Modulations as suggested by S. LeGoff et al, “Turbo codes and High Spectral Efficiency Modulation”, In Proc. IEEE ICC'94, May 1994, New Orleans; P. Robertson et al, “Novel Coded modulation scheme employing Turbo codes”, Electronics Letters, Aug. 31, 1995, Vol. 31, No. 18; and S. Benedetto et al, “Concatenated Trellis Coded Modulation”, In Proc. IEEE ICC'96. All these schemes are based on G. Ungerboeck's Trellis Coded Modulation (TCM) principle described in “Channel coding with multi-level phase signaling”, IEEE Trans. Inf. Theory, Vol. IT-25, January 82, pp. 55-67, which is now a well established technique in digital communications, where significant coding gains are achieved through signal set expansion rather than sacrificing data rate or bandwidth efficiency.
The fundamental phenomenon which makes reliable wireless transmission difficult is time-varying multi path fading with different weights depending on the mobility of users. Strong attenuations make it impossible for the receiver to determine the transmitted signal unless a less-attenuated replica of the transmitted signal is provided to the receiver. This technique is called diversity and presents the well-established and single most important contributor to reliable wireless communications. Diversity assumes sending multiple copies of a signal, which will suffer independent fading. If enough copies are sent, the chances that all of them are subjected to a deep fade will be small. There are a number of ways to implement diversity including time, frequency, polarization, space, and the like.
Time diversity can be achieved by error-control coding and interleaving, where coding adds redundancy to information data and introduces correlation between symbols in the output code word. Interleaving then scrambles the output of an encoder. If the transmission time interval between two consecutive symbols in the code word after interleaving is larger than the coherence time of the channel, symbols will fade independently and thus, combined with decoding, the input information stream can be recovered.
The classical approach to space or antenna diversity is to use multiple antennas at the receiver and perform combining or selection and switching. If the receiving antennas are sufficiently spaced apart, transmitted signals are received over a number of spatially uncorrelated channels and therefore diversity is achieved. The major problem using the receiver diversity in the downlink direction (base-to-mobile) is cost, size and complexity of the mobile units. Electromagnetic interaction of antenna elements of small platforms prevent implementation of more than two uncorrelated antennas at mobile handsets. Therefore, so far, receiver diversity has been almost exclusively applied in the uplink direction (mobile unit to base station) to improve base station reception quality. A solution to improve downlink performance is to exploit sufficiently spaced multiple antennas at the base station so as to achieve a transmit diversity. A number of transmit diversity schemes have been proposed so far which enable the receiver to discard signals transmitted from each component transmitting antenna. Transmitter and receiver antenna diversity can be combined in order to increase diversity order. As can be gathered from G. J. Fochini Jr. et al, “On limits on wireless communication in a fading environment when using multiple antennas”, Wireless Personal Communication, March 1998, multiple input multiple output (MIMO) wireless channels, apart from introducing diversity, enable increased information theory capacity compared to single antenna systems. Therefore, antenna diversity will be a key solution for future wireless services having high demands on transmission speed and reliability. The so-called Space-Time Coding schemes are focused on merging antenna diversity with appropriate channel coning in order to exploit benefits of both, coding and antenna diversity gains. One of the first design criteria for such codes were derived by J. C. Gucy et al, “Signal Design for Transmitter Diversity Wireless Communication Systems over Rayleigh Fading Channels”, IEEE VTC'96, pp. 136-140. However, the main impetus on research in the field of Space-Time Coding was done by the AT&T Group in V. Tarokh et al, “Space-Time Codes for High Data Rate Wireless Communication: Performance Criterion and Code Construction”, IEEE Trans. Inform. Theory, Vol. 44, No. 2, March 1998, where powerful and bandwidth efficient Space-Time Trellis Codes (STTC) were proposed.
Unlike the TCM approach where coding gain is achieved through signal set expansion, the Space-Time Trellis coding approach suggests an expansion in the antenna space. For example TCM enables 2 bit/s/Hz with 8PSK modulation (i.e. PSK modulation with eight complex constellation points) and single transmitting antenna, while in case of STTC 2 bit/s/Hz is achieved with QPSK (Quadrature Phase Shift Keying) modulation (i.e. PSK modulation with four complex constellation points) and two transmitting antennas. The proposed AT&T STTC is a joint design of coding, modulation and antenna diversity. A communication system with n transmitting and m receiving antennas is considered and data is encoded by a channel encoder which adds redundancy to information data and introduces correlation between symbols in the output code word. The output of the encoder is then passed through a serial-to-parallel converter to form n streams of data. Each stream is then modulated and n modulated streams are sent simultaneously over n transmitting antennas so that the redundancy introduced by the encoder does not lead to a decrease of bandwidth efficiency. Additional diversity is achieved due to the fact that the signals are transmitted over a number of n×m uncorrelated fading channels. At the decoder, a maximum likelihood decoding (MLD) is performed to decode signals received by the m receiving antennas.
However, when compared to different transmit diversity schemes which are not designed to exploit any temporal diversity but only spatial diversity, AT&T STTC only leads to very little performance gain. Thus, AT&T STTC was designed to maximize diversity gain for a given number of transmitting antennas but still has very poor coding gain. So far, there has not been established a systematic way to built more powerful STTCs. Moreover, increasing the complexity (number of states) beyond 16 states even leads to a saturation in additional coding gain.